Cartoon: #DataScientist - sexiest job of the 21st century until ...; What is the Role of the Activation Function in Neural Networks?; LinkedIn Machine Learning team tutorial on building #Recommender system; Create a #Chatbot for #Telegram in #Python to Summarize Text.

PAPIs is the premier forum for the presentation of new machine learning APIs, techniques, architectures and tools to build intelligent applications. It also hosts the world’s 1st startup competition where the jury is an AI.

Predictive analytics can help medical professionals reduce costs, improve outcomes, an increase patient satisfaction. Learn from keynotes, dozens of sessions and workshops how to apply these lessons to your own organization. Use code KDN150 to save.

Who were the most talked about athletes in the 2016 Rio Olympic Games? Which sport was most cited by users? What was the overall sentiment? This analysis by Expert System provides the detailed answers.

Has Deep Learning become synonymous with Artificial Intelligence? Read a discussion on the topic fuelled by the opinions of 7 participating experts, and gain some additional insight into the future of research and technology.

If researchers can’t understand a provided answer, it is not viable. They can’t write about techniques they don’t understand beyond “Here are the numbers. Look how pretty my model is.” Good research, that ain’t.

PAW Government is dedicated to exploring how agencies at all levels of government can use data science to reduce wait times, anticipate community needs, minimize overhead, and improve operational efficiency. Use code KDN150 to save.

Successful analytics in the big data era does not start with data and software. It starts with immersive hands-on training, and goal-driven strategy. Get this training with TMA courseware, which spans all skill levels and analytic team roles - Wash-DC in October or Live Online in November.

At IAPA Advancing Analytics event you can meet and hear from the leading global and local thinkers on big data, predictive analytics, machine learning, sentiment analysis, IoT, and more. Early bird ends 25 August, so get your ticket now.

Check out this excellent (and exhaustive) article on becoming a data scientist, written by someone who spends their day recruiting data scientists. Do yourself a favor and read the whole way through. You won't regret it!

Misinformation has emerged as a key issue for social media platforms. This post will introduce the concept of misinformation and the 8 Key Terms, which provides insights into mining misinformation in social media.

If you're looking for an overview of how to approach (almost) any machine learning problem, this is a good place to start. Read on as a Kaggle competition veteran shares his pipelines and approach to problem-solving.

5 EBooks to Read Before Getting into a #DataScience or #BigData Career; Visualizing 1 Billion Points of #Data Webinar; #Cartoon: Make Data Great Again!; The role of the activation function in a #NeuralNetwork

The first-ever Predictive Analytics World conference dedicated to Financial Services will be held this October 23-27 in New York. Register now for early bird pricing, and save an additional $150 with code KDN150.

Beginner's Guide to Neural Networks with R; 5 EBooks to Read Before Getting into A Data Science or Big Data Career; Cartoon: Make Data Great Again; Understanding the Bias-Variance Tradeoff: An Overview

Whenever there is a Big Data conversation, especially in sports, expectations have to be set correctly. Big Data isn’t perfect, but it is a lot better than the more superficial methods of making a judgment.

At the Machine Intelligence Summit in Berlin last week, Jeremy Wyatt, Professor of Robotics and Artificial Intelligence at University of Birmingham, was asked a few questions about his work in mobile robot task planning and manipulation.

In this article we will learn how Neural Networks work and how to implement them with the R programming language! We will see how we can easily create Neural Networks with R and even visualize them. Basic understanding of R is necessary to understand this article.

The inaugural Chief Data Scientist Forum will be the premier event for high-level data science practitioners, containing essential content and new ideas to develop the leadership role for data science. Use code KDCDS to save on registration.

Roland Memisevic, Assistant Professor at the University of Montreal and Chief Scientist at Twenty Billion Neurons, explores ideas on rethinking unsupervised learning, which he feels may explain what scientists have been doing wrong.

Details on the ongoing MICCAI 2016 Cancer Radiomics Challenge, organized by University of Texas MD Anderson Cancer Center radiation oncology team, hosted on Kaggle, and being held until September 12th.

A model's ability to minimize bias and minimize variance are often thought of as 2 opposing ends of a spectrum. Being able to understand these two types of errors are critical to diagnosing model results.

This post is the first place prize recipient in the recent KDnuggets blog contest. Auto-sklearn is an open-source Python tool that automatically determines effective machine learning pipelines for classification and regression datasets. It is built around the successful scikit-learn library and won the recent AutoML challenge.

Where are insurers in adopting blockchain technology and what are the benefits? Insurance Nexus conducted exclusive interviews with Everledger, Guardtime and CGSC and created an exclusive white paper which you can freely download.

This post discusses some considerations, options, and opportunities for automating aspects of data science and machine learning. It is the second place recipient (tied) in the recent KDnuggets blog contest.

PAW Financial focuses on analytics needs of banks, insurance companies, credit card companies, investment firms, and other financial institutions. Book now for the early bird rates, and save extra with code KDN150.

Check Big Data Innovation, Internet of Things, and Data Visualization Summits in Boston, Sep 8-9, 2016. The program is filling out with new sessions being added every week - the depth and breadth of content covered is unrivaled. Use code KD10 for 10% off All Access path.

PMML is an application and system independent format for statistical and data mining models. Key PMML 4.3 features include Improved support for post-processing, model types, and model elements, and new models for Gaussian Process and Bayesian Networks. Check PMML session at KDD-16.

This post provides a simplifying framework, an ontology for Machine Learning and some important developments in dynamical machine learning. From first hand Data Science product experience, the author suggests how best to execute Data Science projects.